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University of Pretoria
1.
[No author].
Statistical analysis of grouped data
.
Degree: 2011, University of Pretoria
URL: http://upetd.up.ac.za/thesis/available/etd-07012008-072755/ 
► The maximum likelihood (ML) estimation procedure of Matthews and Crowther (1995: A maximum likelihood estimation procedure when modelling in terms of constraints. South African Statistical…
(more)
▼ The maximum likelihood (ML) estimation procedure of
Matthews and Crowther (1995: A maximum likelihood estimation
procedure when modelling in terms of constraints. South African
Statistical Journal, 29, 29-51) is utilized to fit a continuous
distribution to a grouped
data set. This grouped
data set may be a
single frequency distribution or various frequency distributions
that arise from a cross classification of several factors in a
multifactor design. It will also be shown how to fit a bivariate
normal distribution to a two-way contingency table where the two
underlying continuous variables are jointly normally distributed.
This thesis is organized in three different parts, each playing a
vital role in the explanation of analysing grouped
data with the ML
estimation of Matthews and Crowther. In Part I the ML estimation
procedure of Matthews and Crowther is formulated. This procedure
plays an integral role and is implemented in all three parts of the
thesis. In Part I the exponential distribution is fitted to a
grouped
data set to explain the technique. Two different
formulations of the constraints are employed in the ML estimation
procedure and provide identical results. The justification of the
method is further motivated by a simulation study. Similar to the
exponential distribution, the estimation of the normal distribution
is also explained in detail. Part I is summarized in Chapter 5
where a general method is outlined to fit continuous distributions
to a grouped
data set. Distributions such as the Weibull, the
log-logistic and the Pareto distributions can be fitted very
effectively by formulating the vector of constraints in terms of a
linear model. In Part II it is explained how to model a grouped
response variable in a multifactor design. This multifactor design
arise from a cross classification of the various factors or
independent variables to be analysed. The cross classification of
the factors results in a total of T cells, each containing a
frequency distribution. Distribution fitting is done simultaneously
to each of the T cells of the multifactor design. Distribution
fitting is also done under the additional constraints that the
parameters of the underlying continuous distributions satisfy a
certain structure or design. The effect of the factors on the
grouped response variable may be evaluated from this fitted design.
Applications of a single-factor and a two-factor model are
considered to demonstrate the versatility of the technique. A
two-way contingency table where the two variables have an
underlying bivariate normal distribution is considered in Part III.
The estimation of the bivariate normal distribution reveals the
complete underlying continuous structure between the two variables.
The ML estimate of the correlation coefficient ρ is used to great
effect to describe the relationship between the two variables.
Apart from an application a simulation study is also provided to
support the method proposed.
Advisors/Committee Members: Prof C F Smit (advisor).
Subjects/Keywords: Grouped data set;
UCTD
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APA (6th Edition):
author], [. (2011). Statistical analysis of grouped data
. (Doctoral Dissertation). University of Pretoria. Retrieved from http://upetd.up.ac.za/thesis/available/etd-07012008-072755/
Chicago Manual of Style (16th Edition):
author], [No. “Statistical analysis of grouped data
.” 2011. Doctoral Dissertation, University of Pretoria. Accessed March 01, 2021.
http://upetd.up.ac.za/thesis/available/etd-07012008-072755/.
MLA Handbook (7th Edition):
author], [No. “Statistical analysis of grouped data
.” 2011. Web. 01 Mar 2021.
Vancouver:
author] [. Statistical analysis of grouped data
. [Internet] [Doctoral dissertation]. University of Pretoria; 2011. [cited 2021 Mar 01].
Available from: http://upetd.up.ac.za/thesis/available/etd-07012008-072755/.
Council of Science Editors:
author] [. Statistical analysis of grouped data
. [Doctoral Dissertation]. University of Pretoria; 2011. Available from: http://upetd.up.ac.za/thesis/available/etd-07012008-072755/
University of Windsor
2.
Singh, Harjeet.
Performance Evaluation of Weighted Greedy Algorithm in Resource Management.
Degree: MS, Computer Science, 2018, University of Windsor
URL: https://scholar.uwindsor.ca/etd/7397
► Set covering is a well-studied classical problem with many applications across different fields. More recent work on this problem has taken into account the parallel…
(more)
▼ Set covering is a well-studied classical problem with many applications across different fields. More recent work on this problem has taken into account the parallel computing architecture, the datasets at scale, the properties of the datasets, etc. Within the context of web crawling where the
data follow the lognormal distribution, a weighted greedy algorithm has been proposed in the literature and demonstrated to outperform the traditional one. In the present work, we evaluate the performance of the weighted greedy algorithm using an open-source dataset in the context of resource management. The
data are sampled from a given roadmap with 1.9 millions of nodes. Our research includes three different cost definitions i.e. location cost, driving cost and infrastructure cost. We also consider the different coverage radius to model possible parameters in the application. Our experiment results show that weighted greedy algorithm outperforms the greedy algorithm by 8% in average for all three different cost definitions.
Advisors/Committee Members: Chen, Jessica.
Subjects/Keywords: big data; set covering algorithms
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APA (6th Edition):
Singh, H. (2018). Performance Evaluation of Weighted Greedy Algorithm in Resource Management. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/7397
Chicago Manual of Style (16th Edition):
Singh, Harjeet. “Performance Evaluation of Weighted Greedy Algorithm in Resource Management.” 2018. Masters Thesis, University of Windsor. Accessed March 01, 2021.
https://scholar.uwindsor.ca/etd/7397.
MLA Handbook (7th Edition):
Singh, Harjeet. “Performance Evaluation of Weighted Greedy Algorithm in Resource Management.” 2018. Web. 01 Mar 2021.
Vancouver:
Singh H. Performance Evaluation of Weighted Greedy Algorithm in Resource Management. [Internet] [Masters thesis]. University of Windsor; 2018. [cited 2021 Mar 01].
Available from: https://scholar.uwindsor.ca/etd/7397.
Council of Science Editors:
Singh H. Performance Evaluation of Weighted Greedy Algorithm in Resource Management. [Masters Thesis]. University of Windsor; 2018. Available from: https://scholar.uwindsor.ca/etd/7397
University of Waterloo
3.
Khaleghi, Bahador.
Distributed Random Set Theoretic Soft/Hard Data Fusion.
Degree: 2012, University of Waterloo
URL: http://hdl.handle.net/10012/6842
► Research on multisensor data fusion aims at providing the enabling technology to combine information from several sources in order to form a unifi ed picture.…
(more)
▼ Research on multisensor data fusion aims at providing the enabling technology to combine
information from several sources in order to form a unifi ed picture. The literature
work on fusion of conventional data provided by non-human (hard) sensors is vast and
well-established. In comparison to conventional fusion systems where input data are generated
by calibrated electronic sensor systems with well-defi ned characteristics, research
on soft data fusion considers combining human-based data expressed preferably in unconstrained
natural language form. Fusion of soft and hard data is even more challenging, yet
necessary in some applications, and has received little attention in the past. Due to being
a rather new area of research, soft/hard data fusion is still in a
edging stage with even
its challenging problems yet to be adequately de fined and explored.
This dissertation develops a framework to enable fusion of both soft and hard data
with the Random Set (RS) theory as the underlying mathematical foundation. Random
set theory is an emerging theory within the data fusion community that, due to its powerful
representational and computational capabilities, is gaining more and more attention among
the data fusion researchers. Motivated by the unique characteristics of the random set
theory and the main challenge of soft/hard data fusion systems, i.e. the need for a unifying
framework capable of processing both unconventional soft data and conventional hard data,
this dissertation argues in favor of a random set theoretic approach as the first step towards
realizing a soft/hard data fusion framework.
Several challenging problems related to soft/hard fusion systems are addressed in the
proposed framework. First, an extension of the well-known Kalman lter within random
set theory, called Kalman evidential filter (KEF), is adopted as a common data processing
framework for both soft and hard data. Second, a novel ontology (syntax+semantics)
is developed to allow for modeling soft (human-generated) data assuming target tracking
as the application. Third, as soft/hard data fusion is mostly aimed at large networks of
information processing, a new approach is proposed to enable distributed estimation of
soft, as well as hard data, addressing the scalability requirement of such fusion systems.
Fourth, a method for modeling trust in the human agents is developed, which enables the
fusion system to protect itself from erroneous/misleading soft data through discounting
such data on-the-fly. Fifth, leveraging the recent developments in the RS theoretic data
fusion literature a novel soft data association algorithm is developed and deployed to extend
the proposed target tracking framework into multi-target tracking case. Finally, the
multi-target tracking framework is complemented by introducing a distributed classi fication
approach applicable to target classes described with soft human-generated data.
In addition, this dissertation presents a novel data-centric taxonomy of data fusion
…
Subjects/Keywords: Data Fusion; Random Set Theory
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APA (6th Edition):
Khaleghi, B. (2012). Distributed Random Set Theoretic Soft/Hard Data Fusion. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/6842
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Khaleghi, Bahador. “Distributed Random Set Theoretic Soft/Hard Data Fusion.” 2012. Thesis, University of Waterloo. Accessed March 01, 2021.
http://hdl.handle.net/10012/6842.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Khaleghi, Bahador. “Distributed Random Set Theoretic Soft/Hard Data Fusion.” 2012. Web. 01 Mar 2021.
Vancouver:
Khaleghi B. Distributed Random Set Theoretic Soft/Hard Data Fusion. [Internet] [Thesis]. University of Waterloo; 2012. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/10012/6842.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Khaleghi B. Distributed Random Set Theoretic Soft/Hard Data Fusion. [Thesis]. University of Waterloo; 2012. Available from: http://hdl.handle.net/10012/6842
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Delft University of Technology
4.
van Engelshoven, Yuup (author).
Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:32bf01ba-b6c6-410e-b0e1-b15d95eb05d9
► Payment Channel Networks(PCN) utilize payment channels with an established link capacity between two nodes to route transactions over multiple links to carry out transactions. Such…
(more)
▼ Payment Channel Networks(PCN) utilize payment channels with an established link capacity between two nodes to route transactions over multiple links to carry out transactions. Such transactions can support a blockchain due to the transactions happening off-chain, i.e., not requiring any information to be published to a ledger. PCNs can help aid in the scalability of blockchains, by moving transactions off-chain not all transactions need to be stored on the blockchain, reducing the amount of
data that needs to be stored on the blockchain. Lightning is the PCN implementation that makes use of Bitcoins blockchain. As transactions occur over the network the capacity of the link may vary over time between two nodes. This change may lead to the link being only available from one side. If enough links become unavailable then processing transactions may take longer or in the worst-case scenario transactions may no longer be feasible in the network. To help avoid these short-comings in PCN strategies can be designed in path-based transaction algorithms to help keep links capable of handling transactions bidirectionally. This work presents two such algorithms, the Passive Merchant and Active Merchant. Additionally, two synthetic
data-
set models are proposed to help evaluate the effectiveness of the Merchant algorithms, due to a lack of
data-sets in this field. In the evaluation two different topologies are examined to evaluate the impact a graph has on the success rate of transactions within a PCN. The evaluation of the The Merchant algorithms is simulation based, experiments evaluated how different algorithms effected the success rate of transactions. The simulation did indicate that the algorithms were able to help increase the success rate of transactions, up to 8%. As these algorithms are embedded in the transaction process of a payment the algorithms are a first of there kind, other solutions have been proposed for rebalancing as a separate protocol. In addition to being the first to propose transaction embedded rebalancing algorithms, no other synthetic
data-
set models for PCN have been proposed. The synthetic
data-
set models may allow this area of research to be have constant
data-sets that are used to evaluate the effectiveness of path-based transactions.
Advisors/Committee Members: Roos, Stefanie (mentor), Epema, Dick (graduation committee), Pawelczak, Przemek (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Blockchain; Payment Channel Network; SpeedyMurmurs; Data-set; Synthetic Data-set
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APA (6th Edition):
van Engelshoven, Y. (. (2019). Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:32bf01ba-b6c6-410e-b0e1-b15d95eb05d9
Chicago Manual of Style (16th Edition):
van Engelshoven, Yuup (author). “Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks.” 2019. Masters Thesis, Delft University of Technology. Accessed March 01, 2021.
http://resolver.tudelft.nl/uuid:32bf01ba-b6c6-410e-b0e1-b15d95eb05d9.
MLA Handbook (7th Edition):
van Engelshoven, Yuup (author). “Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks.” 2019. Web. 01 Mar 2021.
Vancouver:
van Engelshoven Y(. Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 01].
Available from: http://resolver.tudelft.nl/uuid:32bf01ba-b6c6-410e-b0e1-b15d95eb05d9.
Council of Science Editors:
van Engelshoven Y(. Designing and Evaluating Rebalancing Algorithms for Payment Channel Networks. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:32bf01ba-b6c6-410e-b0e1-b15d95eb05d9
5.
Pandey, Prateek.
Forecasting in data pauperism;.
Degree: Computer Science Engineering, 2015, Jaypee University of Engineering and Technology, Guna
URL: http://shodhganga.inflibnet.ac.in/handle/10603/42727
► Any forecasting method requires some evidences on the basis of which a future event can be estimated Sometimes these evidences are present as numerical quantities…
(more)
▼ Any forecasting method requires some evidences on
the basis of which a future event can be estimated Sometimes these
evidences are present as numerical quantities and the employable
techniques are called quantitative forecasting techniques Sometimes
the evidences cannot or should not be represented as numerical
quantities instead they may better be represented as linguistic
values In such cases quantitative forecasting techniques are not
useful and a fuzzy analysis is the only solution A good quality of
these fuzzy based forecasting techniques is that the constraints
that are applicable over traditional quantitative forecasting
techniques are relaxed in the case of fuzzy based techniques For
example minimum requirement for evidences in the traditional
quantitative forecasting techniques is 50 and more than 100 are
preferable, whereas a fuzzy based forecasting technique is found to
produce good forecasts with as low as 32 evidences In some cases
these evidences may be missing or unavailable which is often the
case with new or innovative products The forecasting techniques
that are employable in such conditions are called qualitative
forecasting techniques Such techniques make use of experts opinions
and complex decision making in order to derive useful forecasts
This involvement of human experts makes the process vulnerable to a
number of biases and imprecision Again to deal with such
imprecision to some extent a fuzzy assessment of the problem may be
useful newlineThe thesis examines the literature on forecasting to
find the techniques of merit when the evidences are either limited
or not present at all The objective of the thesis is to find an
answer to the poor forecasting accuracy obtained in case of the
dearth of evidences newlineData pauperism in the context of this
work refers to the two states of data under which forecasting are
performed newlineAn absolute absence no prior data are available to
perform any evidence based forecasting newline
newline
Advisors/Committee Members: Kumar, Shishir and Srivastava,
Sandeep.
Subjects/Keywords: Clustering Processing; Data Forecasting; Data Pauperism; Fuzzy Set Theory
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APA (6th Edition):
Pandey, P. (2015). Forecasting in data pauperism;. (Thesis). Jaypee University of Engineering and Technology, Guna. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/42727
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Pandey, Prateek. “Forecasting in data pauperism;.” 2015. Thesis, Jaypee University of Engineering and Technology, Guna. Accessed March 01, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/42727.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Pandey, Prateek. “Forecasting in data pauperism;.” 2015. Web. 01 Mar 2021.
Vancouver:
Pandey P. Forecasting in data pauperism;. [Internet] [Thesis]. Jaypee University of Engineering and Technology, Guna; 2015. [cited 2021 Mar 01].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/42727.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Pandey P. Forecasting in data pauperism;. [Thesis]. Jaypee University of Engineering and Technology, Guna; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/42727
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Princeton University
6.
Larkin, Daniel.
Compressing Trees with a Sledgehammer
.
Degree: PhD, 2016, Princeton University
URL: http://arks.princeton.edu/ark:/88435/dsp011g05ff012
► A variety of problems can be solved more efficiently with the use of compressed trees. The compressed tree method is flexible and can be applied…
(more)
▼ A variety of problems can be solved more efficiently with the use of compressed trees. The compressed tree method is flexible and can be applied in different ways to solutions for many problems including disjoint
set union, nested
set union, and path evaluation.
The central contribution of this thesis is a unified framework for the analysis of the compressed tree method and a meta-theorem that proves an inverse-Ackermann-type bound for a class of algorithms. The meta-theorem requires only that the compaction method be well-structured and that the other operations maintain a forest structure that admits a well-behaved rank function. These are the weakest known conditions of any analysis to-date that proves such a bound.
We use the framework to give a clean, compact alternative analysis of all but one of the known efficient algorithms for disjoint
set union; we provide an explicit proof of optimality for the remaining known optimal method, splicing by rank, which was left as an exercise by Tarjan and van Leeuwen; we prove that a new algorithm for disjoint
set union called randomized linking is optimal, giving theoretical backing for some recent experimental results; and finally we proceed to explore the nested
set union problem, giving an optimal algorithm for any constant number of partitions as well as a few alternatives for the restricted case of two partitions.
Advisors/Committee Members: Tarjan, Robert (advisor).
Subjects/Keywords: algorithms;
compressed trees;
data structures;
disjoint set union;
nested set union;
union-find
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APA (6th Edition):
Larkin, D. (2016). Compressing Trees with a Sledgehammer
. (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp011g05ff012
Chicago Manual of Style (16th Edition):
Larkin, Daniel. “Compressing Trees with a Sledgehammer
.” 2016. Doctoral Dissertation, Princeton University. Accessed March 01, 2021.
http://arks.princeton.edu/ark:/88435/dsp011g05ff012.
MLA Handbook (7th Edition):
Larkin, Daniel. “Compressing Trees with a Sledgehammer
.” 2016. Web. 01 Mar 2021.
Vancouver:
Larkin D. Compressing Trees with a Sledgehammer
. [Internet] [Doctoral dissertation]. Princeton University; 2016. [cited 2021 Mar 01].
Available from: http://arks.princeton.edu/ark:/88435/dsp011g05ff012.
Council of Science Editors:
Larkin D. Compressing Trees with a Sledgehammer
. [Doctoral Dissertation]. Princeton University; 2016. Available from: http://arks.princeton.edu/ark:/88435/dsp011g05ff012
NSYSU
7.
Yang, Chih-Chin.
A Spam Filter Based on Reinforcement and Collaboration.
Degree: Master, Information Management, 2008, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-164951
► Growing volume of spam mails have not only decreased the productivity of people but also become a security threat on the Internet. Mail servers should…
(more)
▼ Growing volume of spam mails have not only decreased the productivity of people but also become a security threat on the Internet. Mail servers should have abilities to filter out spam mails which change time by time precisely and manage increasing spam rules which generated by mail servers automatically and effectively. Most paper only focused on single aspect (especially for spam rule generation) to prevent spam mail. However, in real word, spam prevention is not just applying
data mining algorithm for rule generation. To filter out spam mails correctly in a real world, there are still many issues should be considered in addition to spam rule generation.
In this paper, we integrate three modules to form a complete anti-spam system, they are spam rule generation module, spam rule reinforcement module and spam rule exchange module. In this paper, rule-based
data mining approach is used to generate exchangeable spam rules. The feedback of userâs returns is reinforced spam rule. The distributing spam rules are exchanged through machine-readable XML format. The results of experiment draw the following conclusion: (1) The spam filter can filter out the Chinese mails by analyzing the header characteristics. (2) Rules exchanged among mail improve the spam recall and accuracy of mail servers. (3) Rules reinforced improve the effectiveness of spam rule.
Advisors/Committee Members: none (chair), Chia-Mei Chen (committee member), none (chair), Bing-Chiang Jeng (committee member).
Subjects/Keywords: Spam; Data Mining and Artificial Intelligence; Collaborative; Rough Set Theory
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APA (6th Edition):
Yang, C. (2008). A Spam Filter Based on Reinforcement and Collaboration. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-164951
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Yang, Chih-Chin. “A Spam Filter Based on Reinforcement and Collaboration.” 2008. Thesis, NSYSU. Accessed March 01, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-164951.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Yang, Chih-Chin. “A Spam Filter Based on Reinforcement and Collaboration.” 2008. Web. 01 Mar 2021.
Vancouver:
Yang C. A Spam Filter Based on Reinforcement and Collaboration. [Internet] [Thesis]. NSYSU; 2008. [cited 2021 Mar 01].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-164951.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Yang C. A Spam Filter Based on Reinforcement and Collaboration. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-164951
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
NSYSU
8.
Wang, Tse-yao.
The study of data preprocessing difference to impact the botnet detection performance.
Degree: PhD, Information Management, 2016, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523
► Many studies employ machine learning to detect botnet C&C communications traffic quite effective. If the former data handled properly, it will affect the final detection…
(more)
▼ Many studies employ machine learning to detect botnet C&C communications traffic quite effective. If the former
data handled properly, it will affect the final detection performance. So that is must be complete
data preprocessing to facilitate operation analysis program. The Botnet traffic based detection research lack of general guidance
data conversion. This study presents four coding rules and chose the Rough
Set, Support Vector Machine and Naïve Bayes as experimental classifier. Initial experiments used the Rough
Set and Las Vegas Filter as a feature selection algorithm discussed when the feature selection, the best
data coding rules. Based on the results of the initial experiments conducted subsequent experiments were compared using feature selection on detection performance, the final experiments are compared using feature selection on detection performance by analyzing experimental
data concluded that
data coding rules and design guidelines. The study has two important findings. Firstly, carefully distinguishing Empty, NULL, and the meanings of
data can avoid confusing situations of
data coding and negative detection result of the system. Secondly, the minor difference of the
data contents should be ignored to find a stronger correlation among the similar events when machine learning detection models are adopted. Hence, the Rough
Set to verify the effective conduct of feature selection, helps eliminate redundant
data, Acceleration analysis time and improves detection accuracy.
Advisors/Committee Members: Ping Wang (chair), Keng-Pei Lin (chair), Chih-Ping Wei (chair), Chen-chia Mei (committee member), Gu Hsin Lai (chair).
Subjects/Keywords: data transformation; machine learning; Botnet detection; Rough Set Theory; feature selection
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APA ·
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Manager
APA (6th Edition):
Wang, T. (2016). The study of data preprocessing difference to impact the botnet detection performance. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523
Chicago Manual of Style (16th Edition):
Wang, Tse-yao. “The study of data preprocessing difference to impact the botnet detection performance.” 2016. Doctoral Dissertation, NSYSU. Accessed March 01, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523.
MLA Handbook (7th Edition):
Wang, Tse-yao. “The study of data preprocessing difference to impact the botnet detection performance.” 2016. Web. 01 Mar 2021.
Vancouver:
Wang T. The study of data preprocessing difference to impact the botnet detection performance. [Internet] [Doctoral dissertation]. NSYSU; 2016. [cited 2021 Mar 01].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523.
Council of Science Editors:
Wang T. The study of data preprocessing difference to impact the botnet detection performance. [Doctoral Dissertation]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0613116-112523
University of Rochester
9.
Altun, H. Oktay (1978 - ); Bocko, Mark Frederick (1956 - ).
Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond.
Degree: PhD, 2012, University of Rochester
URL: http://hdl.handle.net/1802/21220
► The digital revolution is affecting our daily activities, changing our habits and indeed reshaping cultures around the world. The intellectual products of today are now…
(more)
▼ The digital revolution is affecting our daily
activities, changing our habits and indeed
reshaping cultures
around the world. The intellectual products of today are now
primarily
created and distributed in digital format. Furthermore,
the Internet has become a pervasive
communication and sharing
network. All of these factors naturally have led to concerns over
the security of digital information. Among the many proposed
solutions to such concerns,
digital watermarking has proven to be
unique by its not requiring a safe auxiliary communication
channel. However, proposed watermarking techniques and attacks
against such
methods make the watermarking problem dynamic,
complicated, and challenging.
We show that several of the
requirements in watermarking applications can be
mapped onto
convex constraints or can be closely approximated as convex
constraints.
These include watermark detectability, robustness to
added noise, multiple watermark detectability,
imperceptibility,
robustness against lossy compression, robustness against lowpass
filtering attacks, robustness against non-linear soft/hard wavelet
shrinkage denoising
attacks, and fragility under aggressive
compression. This approach allows determination of
feasible
solutions by using the powerful method of projections onto convex
sets (POCS). The
POCS algorithm is employed to create a
watermarked image that satisfies all watermarking
requirements
simultaneously.
We further extend the POCS formulation of
watermark design into constrained
optimization formulations for
the scenarios where a single performance criterion may need
to be
optimized. We propose an algorithmic framework for solving these
optimal embedding
problems via a multi-step feasibility approach
that combines projections onto convex sets
(POCS) based
feasibility watermarking with a bisection parameter search for
determining
the optimum value of the objective function and the
optimum watermarked image. The
framework is general and can handle
optimum watermark embedding problems with convex
and quasi-convex
formulations of constraints and furthermore the algorithm has
assured
convergence to the global optimum. The proposed scheme is
a natural extension of set-theoretic
watermark design and provides
a link between convex feasibility and optimization
formulations
for watermark embedding. We demonstrate a number of optimal
watermark
embeddings in the proposed framework corresponding to
maximal robustness to additive
noise, maximal robustness against
compression, minimal frequency weighted perceptual
distortion, and
minimal texture watermark visibility. Experimental results
demonstrate
that the framework is effective in optimizing the
desired characteristic while meeting the
constraints. The results
also highlight both anticipated and unanticipated competition
between the common requirements for watermark embedding.
Utilizing
the same framework, we also pose the problem of determining a
steganographic
image as a feasibility problem subject to
constraints of data communication,…
Subjects/Keywords: Multimedia security; Data hiding; Set theory; Fingerprinting; Watermarking
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CSE |
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APA (6th Edition):
Altun, H. Oktay (1978 - ); Bocko, M. F. (. -. ). (2012). Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/21220
Chicago Manual of Style (16th Edition):
Altun, H. Oktay (1978 - ); Bocko, Mark Frederick (1956 - ). “Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond.” 2012. Doctoral Dissertation, University of Rochester. Accessed March 01, 2021.
http://hdl.handle.net/1802/21220.
MLA Handbook (7th Edition):
Altun, H. Oktay (1978 - ); Bocko, Mark Frederick (1956 - ). “Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond.” 2012. Web. 01 Mar 2021.
Vancouver:
Altun, H. Oktay (1978 - ); Bocko MF(-). Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond. [Internet] [Doctoral dissertation]. University of Rochester; 2012. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/1802/21220.
Council of Science Editors:
Altun, H. Oktay (1978 - ); Bocko MF(-). Set theoretic framework for multimedia security and data
hiding: applications to watermarking, steganography,
fingerprinting, and beyond. [Doctoral Dissertation]. University of Rochester; 2012. Available from: http://hdl.handle.net/1802/21220
University of Alberta
10.
Satsangi, Amit.
Data mining using contrast-sets: A comparative study.
Degree: MS, Department of Computing Science, 2011, University of Alberta
URL: https://era.library.ualberta.ca/files/dv13zt35j
► Comparative analysis is an essential part of understanding how and why things work the way they do. Why postgraduate degree holders really earn more money…
(more)
▼ Comparative analysis is an essential part of
understanding how and why things work the way they do. Why
postgraduate degree holders really earn more money than those with
an undergraduate degree? What factors contribute to pre-term
births? Why are some students more successful than others? The
above questions require comparison between various classes.
Contrast-set mining was first proposed as a way to identify
attributes that significantly differentiate between various classes
(groups). While contrast-set mining has been widely applied for
differentiating between different groups however, no clear picture
seems to have emerged regarding how to extract the contrast-sets
that discriminate most between the classes. In this thesis we try
to address the problem of finding meaningful contrast sets by
applying Association Rule Mining. We report a new family of
contrast-sets, and we present and compare the results of our
experiments with the well known algorithm for contrast-set mining -
STUCCO.
Subjects/Keywords: Contrast-set mining; Group contrasting; Contrast-sets; Data-mining
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APA (6th Edition):
Satsangi, A. (2011). Data mining using contrast-sets: A comparative study. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/dv13zt35j
Chicago Manual of Style (16th Edition):
Satsangi, Amit. “Data mining using contrast-sets: A comparative study.” 2011. Masters Thesis, University of Alberta. Accessed March 01, 2021.
https://era.library.ualberta.ca/files/dv13zt35j.
MLA Handbook (7th Edition):
Satsangi, Amit. “Data mining using contrast-sets: A comparative study.” 2011. Web. 01 Mar 2021.
Vancouver:
Satsangi A. Data mining using contrast-sets: A comparative study. [Internet] [Masters thesis]. University of Alberta; 2011. [cited 2021 Mar 01].
Available from: https://era.library.ualberta.ca/files/dv13zt35j.
Council of Science Editors:
Satsangi A. Data mining using contrast-sets: A comparative study. [Masters Thesis]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/dv13zt35j
University of Michigan
11.
Dutta, Diptavo.
Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis.
Degree: PhD, Biostatistics, 2019, University of Michigan
URL: http://hdl.handle.net/2027.42/151689
► As association studies continue to advance, more efficient statistical methods are required to fully utilize existing data and to provide insight into genetic architecture of…
(more)
▼ As association studies continue to advance, more efficient statistical methods are required to fully utilize existing
data and to provide insight into genetic architecture of complex traits. Identifying association for a
set of phenotypes or with respect to a
set of variants can be particularly useful for understanding how biological networks might be affecting the patho-physiology of outcomes. In this dissertation, I attempt to develop computationally efficient statistical methods that facilitate insights into the mechanism of complex traits and understanding of their underlying biology.
In Chapter II, I propose a generalized framework for gene-based tests with multiple correlated phenotypes. In genetic association analysis, a joint test of multiple correlated phenotypes can increase power to identify sets of trait-associated variants within genes or regions of interest. Existing multi-phenotype tests for rare variants make specific assumptions about the patterns of association with underlying causal variants and the violation of these assumptions can reduce power to detect association. In this project we develop a general framework for testing pleiotropic effects of rare variants on multiple continuous phenotypes using multivariate kernel regression (Multi-SKAT). To increase power of detecting association across tests with different kernel matrices, we developed a fast and accurate approximation of the significance of the minimum observed p-value across tests. To account for related individuals, our framework uses random effects for the kinship matrix. Using simulated and exome-array
data from the METSIM study, we show that Multi-SKAT can increase power over single-phenotype SKAT-O test and existing multiple phenotype tests, while maintaining type I error rate.
In Chapter III, I extend Multi-SKAT to a meta-analysis strategy, namely Meta-MultiSKAT, to combine results from several studies. Our method involves extracting score statistics and phenotype adjusted variant relationship matrix from individual studies which are then combined using a kernel that models the heterogeneity of effects between the studies. The proposed method accommodates situations where one or more phenotypes have not been observed in a particular study and studies have different correlation patterns among the phenotypes. With minor modifications our method can be used to test the combined effects of common and rare variants in a region, as well as incorporate functional information on individual variants. Meta-analysis of 4 white blood cell subtype traits from the MGI and SardiNIA studies show that Meta-MultiSKAT can identify associations which were not identified by existing methods and were not significant in individual studies.
In Chapter IV, I propose a subset based approach for gene-
set (pathway) association analysis using variant level summary statistics. Existing gene-
set association (GSA) methods can have low statistical power when only a small fraction of the genes is associated with the phenotype and interpreting results in terms…
Advisors/Committee Members: Lee, Seunggeun Shawn (committee member), Sen, Ananda (committee member), Boehnke, Michael Lee (committee member), Scott, Laura Jean (committee member).
Subjects/Keywords: Multiple phenotypes; Gene-set; Kernel regression; Statistics and Numeric Data; Science
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CSE |
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APA (6th Edition):
Dutta, D. (2019). Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151689
Chicago Manual of Style (16th Edition):
Dutta, Diptavo. “Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis.” 2019. Doctoral Dissertation, University of Michigan. Accessed March 01, 2021.
http://hdl.handle.net/2027.42/151689.
MLA Handbook (7th Edition):
Dutta, Diptavo. “Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis.” 2019. Web. 01 Mar 2021.
Vancouver:
Dutta D. Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/2027.42/151689.
Council of Science Editors:
Dutta D. Statistical Methods for Multiple Phenotypes and Gene-Set Association Analysis. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151689
University of North Texas
12.
Liu, Siyuan.
Learning from small data set for object recognition in mobile platforms.
Degree: 2016, University of North Texas
URL: https://digital.library.unt.edu/ark:/67531/metadc849633/
► Did you stand at a door with a bunch of keys and tried to find the right one to unlock the door? Did you hold…
(more)
▼ Did you stand at a door with a bunch of keys and tried to find the right one to unlock the door? Did you hold a flower and wonder the name of it? A need of object recognition could rise anytime and any where in our daily lives. With the development of mobile devices object recognition applications become possible to provide immediate assistance. However, performing complex tasks in even the most advanced mobile platforms still faces great challenges due to the limited computing resources and computing power.
In this thesis, we present an object recognition system that resides and executes within a mobile device, which can efficiently extract image features and perform learning and classification. To account for the computing constraint, a novel feature extraction method that minimizes the
data size and maintains
data consistency is proposed. This system leverages principal component analysis method and is able to update the trained classifier when new examples become available . Our system relieves users from creating a lot of examples and makes it user friendly.
The experimental results demonstrate that a learning method trained with a very small number of examples can achieve recognition accuracy above 90% in various acquisition conditions. In addition, the system is able to perform learning efficiently.
Advisors/Committee Members: Yuan, Xiaohui, Fu, Song, Takabi, Hassan.
Subjects/Keywords: object recognition; machine learning; mobile platforms; small data set; feature extraction
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13.
Graux, Damien.
On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées.
Degree: Docteur es, Informatique, 2016, Université Grenoble Alpes (ComUE)
URL: http://www.theses.fr/2016GREAM058
► Le Web Sémantique est une extension du Web standardisée par le World Wide Web Consortium. Les différents standards utilisent comme format de base pour les…
(more)
▼ Le Web Sémantique est une extension du Web standardisée par le World Wide Web Consortium. Les différents standards utilisent comme format de base pour les données le Resource Description Framework (rdf) et son langage de requêtes nommé sparql. Plus généralement, le Web Sémantique tend à orienter l’évolution du Web pour permettre de trouver et de traiter l’information plus facilement. L'augmentation des volumes de données rdf disponibles tend à faire rendre standard la distribution des jeux de données. Par conséquent, des évaluateurs de requêtes sparql efficaces et distribués sont de plus en plus nécessaires. Pour faire face à ces challenges, nous avons commencé par comparer plusieurs évaluateurs sparql distribués de l'état-de-l'art tout en adaptant le jeu de métriques considéré. Ensuite, une analyse guidée par des cas typiques d'utilisation nous a conduit à définir de nouveaux champs de développement dans le domaine de l'évaluation distribuée de sparql. Sur la base de ces nouvelles perspectives, nous avons développé plusieurs évaluateurs efficaces pour ces différents cas d'utilisation que nous avons comparé expérimentalement.
The Semantic Web standardized by the World Wide Web Consortium aims at providing a common framework that allows data to be shared and analyzed across applications. Thereby, it introduced as common base for data the Resource Description Framework (rdf) and its query language sparql.Because of the increasing amounts of rdf data available, dataset distribution across clusters is poised to become a standard storage method. As a consequence, efficient and distributed sparql evaluators are needed.To tackle these needs, we first benchmark several state-of-the-art distributed sparql evaluators while adapting the considered set of metrics to a distributed context such as e.g. network traffic. Then, an analysis driven by typical use cases leads us to define new development areas in the field of distributed sparql evaluation. On the basis of these fresh perspectives, we design several efficient distributed sparql evaluators which fit into each of these use cases and whose performances are validated compared with the already benchmarked evaluators. For instance, our distributed sparql evaluator named sparqlgx offers efficient time performances while being resilient to the loss of nodes.
Advisors/Committee Members: Layaida, Nabil (thesis director), Genevès, Pierre (thesis director).
Subjects/Keywords: BigData; Passage à l'échelle; Données; BigData; Scalability; Data set; 004
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Graux, D. (2016). On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées. (Doctoral Dissertation). Université Grenoble Alpes (ComUE). Retrieved from http://www.theses.fr/2016GREAM058
Chicago Manual of Style (16th Edition):
Graux, Damien. “On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées.” 2016. Doctoral Dissertation, Université Grenoble Alpes (ComUE). Accessed March 01, 2021.
http://www.theses.fr/2016GREAM058.
MLA Handbook (7th Edition):
Graux, Damien. “On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées.” 2016. Web. 01 Mar 2021.
Vancouver:
Graux D. On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées. [Internet] [Doctoral dissertation]. Université Grenoble Alpes (ComUE); 2016. [cited 2021 Mar 01].
Available from: http://www.theses.fr/2016GREAM058.
Council of Science Editors:
Graux D. On the efficient distributed evaluation of SPARQL queries : Sur l'évaluation efficace de requêtes SPARQL distribuées. [Doctoral Dissertation]. Université Grenoble Alpes (ComUE); 2016. Available from: http://www.theses.fr/2016GREAM058
University of Pretoria
14.
Crafford, Gretel.
Statistical
analysis of grouped data.
Degree: Statistics, 2007, University of Pretoria
URL: http://hdl.handle.net/2263/25968
► The maximum likelihood (ML) estimation procedure of Matthews and Crowther (1995: A maximum likelihood estimation procedure when modelling in terms of constraints. South African Statistical…
(more)
▼ The maximum likelihood (ML) estimation procedure of
Matthews and Crowther (1995: A maximum likelihood estimation
procedure when modelling in terms of constraints. South African
Statistical Journal, 29, 29-51) is utilized to fit a continuous
distribution to a grouped
data set. This grouped
data set may be a
single frequency distribution or various frequency distributions
that arise from a cross classification of several factors in a
multifactor design. It will also be shown how to fit a bivariate
normal distribution to a two-way contingency table where the two
underlying continuous variables are jointly normally distributed.
This thesis is organized in three different parts, each playing a
vital role in the explanation of analysing grouped
data with the ML
estimation of Matthews and Crowther. In Part I the ML estimation
procedure of Matthews and Crowther is formulated. This procedure
plays an integral role and is implemented in all three parts of the
thesis. In Part I the exponential distribution is fitted to a
grouped
data set to explain the technique. Two different
formulations of the constraints are employed in the ML estimation
procedure and provide identical results. The justification of the
method is further motivated by a simulation study. Similar to the
exponential distribution, the estimation of the normal distribution
is also explained in detail. Part I is summarized in Chapter 5
where a general method is outlined to fit continuous distributions
to a grouped
data set. Distributions such as the Weibull, the
log-logistic and the Pareto distributions can be fitted very
effectively by formulating the vector of constraints in terms of a
linear model. In Part II it is explained how to model a grouped
response variable in a multifactor design. This multifactor design
arise from a cross classification of the various factors or
independent variables to be analysed. The cross classification of
the factors results in a total of T cells, each containing a
frequency distribution. Distribution fitting is done simultaneously
to each of the T cells of the multifactor design. Distribution
fitting is also done under the additional constraints that the
parameters of the underlying continuous distributions satisfy a
certain structure or design. The effect of the factors on the
grouped response variable may be evaluated from this fitted design.
Applications of a single-factor and a two-factor model are
considered to demonstrate the versatility of the technique. A
two-way contingency table where the two variables have an
underlying bivariate normal distribution is considered in Part III.
The estimation of the bivariate normal distribution reveals the
complete underlying continuous structure between the two variables.
The ML estimate of the correlation coefficient ρ is used to great
effect to describe the relationship between the two variables.
Apart from an application a simulation study is also provided to
support the method proposed.
Advisors/Committee Members: Smit, Chris F. (advisor).
Subjects/Keywords: Grouped data
set;
UCTD
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APA ·
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MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Crafford, G. (2007). Statistical
analysis of grouped data. (Doctoral Dissertation). University of Pretoria. Retrieved from http://hdl.handle.net/2263/25968
Chicago Manual of Style (16th Edition):
Crafford, Gretel. “Statistical
analysis of grouped data.” 2007. Doctoral Dissertation, University of Pretoria. Accessed March 01, 2021.
http://hdl.handle.net/2263/25968.
MLA Handbook (7th Edition):
Crafford, Gretel. “Statistical
analysis of grouped data.” 2007. Web. 01 Mar 2021.
Vancouver:
Crafford G. Statistical
analysis of grouped data. [Internet] [Doctoral dissertation]. University of Pretoria; 2007. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/2263/25968.
Council of Science Editors:
Crafford G. Statistical
analysis of grouped data. [Doctoral Dissertation]. University of Pretoria; 2007. Available from: http://hdl.handle.net/2263/25968
Utah State University
15.
Sahu, Vaibhav.
Identifying Criticality in Market Sentiment: A Data Mining Approach.
Degree: MS, Computer Science, 2018, Utah State University
URL: https://digitalcommons.usu.edu/etd/7389
► The aim of this thesis is to study and identify time periods of high activity in commodity and stock market sentiment based on a…
(more)
▼ The aim of this thesis is to study and identify time periods of high activity in commodity and stock market sentiment based on a
data mining approach. The method is to develop tools to extract relevant information from web searches and Twitter feeds based on the tally of certain keywords and their combinations at regular intervals. Periods of high activity are identified by a measure of complexity developed for analysis of living systems. Experiments were conducted to see if the measure of activity could be applied as a predictor of changes in stock market and commodity prices.
Advisors/Committee Members: Nicholas Flann, Vladimir Kulyukin, Xiaojun Qi, ;.
Subjects/Keywords: Data Mining; Information Measure; Set Complexity; Sentiment Analysis; Market; Computer Sciences
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Manager
APA (6th Edition):
Sahu, V. (2018). Identifying Criticality in Market Sentiment: A Data Mining Approach. (Masters Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/7389
Chicago Manual of Style (16th Edition):
Sahu, Vaibhav. “Identifying Criticality in Market Sentiment: A Data Mining Approach.” 2018. Masters Thesis, Utah State University. Accessed March 01, 2021.
https://digitalcommons.usu.edu/etd/7389.
MLA Handbook (7th Edition):
Sahu, Vaibhav. “Identifying Criticality in Market Sentiment: A Data Mining Approach.” 2018. Web. 01 Mar 2021.
Vancouver:
Sahu V. Identifying Criticality in Market Sentiment: A Data Mining Approach. [Internet] [Masters thesis]. Utah State University; 2018. [cited 2021 Mar 01].
Available from: https://digitalcommons.usu.edu/etd/7389.
Council of Science Editors:
Sahu V. Identifying Criticality in Market Sentiment: A Data Mining Approach. [Masters Thesis]. Utah State University; 2018. Available from: https://digitalcommons.usu.edu/etd/7389
Delft University of Technology
16.
Gerling, Jan (author).
Machine Learning for Software Refactoring: a Large-Scale Empirical Study.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:bf649e9c-9d53-4e8c-a91b-f0a6b6aab733
► Refactorings tackle the challenge of architectural degradation of object-oriented software projects by improving its internal structure without changing the behavior. Refactorings improve software quality and…
(more)
▼ Refactorings tackle the challenge of architectural degradation of object-oriented software projects by improving its internal structure without changing the behavior. Refactorings improve software quality and maintainability if applied correctly. However, identifying refactoring opportunities is a challenging problem for developers and researchers alike. In a recent work, machine learning algorithms have shown great potential to solve this problem. This thesis used RefactoringMiner to detect refactorings in open-source Java projects and computed code metrics by static analysis. We defined the refactoring opportunity detection problem as a binary classification problem and deployed machine learning algorithms to solve it. The models classify between a specific refactoring type and a stable class using the metrics as features. Multiple machine learning experiments were designed based on the results of an empirical study of the refactorings. For this work, we created the largest data set of refactorings in Java source code to date, including 92800 open-source projects from GitHub with a total of 33.67 million refactoring samples. The data analysis revealed that Class- and Package-Level refactorings occur most frequently in early development stages of a class, Method- and Variable-Level refactorings are applied uniformly during the development of a class. The machine learning models achieve high performance ranging from 80% to 89% total average accuracy for different configurations of the refactoring opportunity prediction problem on unseen projects. Selecting a high Stable Commit Threshold (K) improves the recall of the models significantly, but also strongly reduces the generalizability of the models. The Random Forest (RF) classifier shows great potential for the refactoring opportunity detection, it can adapt to various configurations of the problem, identifies a large variety of relevant metrics in the data and is able to distinguish different refactoring types. This work shows that for solving the refactoring opportunity detection problem a large variety of metrics is required, as a small set of metrics cannot represent the complexity of the problem.
http://doi.org/10.5281/zenodo.4267824 Appendix: Data Analysis and Machine Learning Experiments ShowEdit http://doi.org/10.5281/zenodo.4267711 Appendix: Refactoring Data Set ShowEdit https://github.com/refactoring-ai/Data-Collection Repository link Refactoring Mining Tool ShowEdit https://github.com/refactoring-ai/Machine-Learning Repository link Machine Learning Pipeline
Computer Science
Advisors/Committee Members: Finavaro Aniche, M. (mentor), van Deursen, A. (graduation committee), Erkin, Z. (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Refactoring; software engineering; machine learning; data set; open source; Java
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APA ·
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Export
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APA (6th Edition):
Gerling, J. (. (2020). Machine Learning for Software Refactoring: a Large-Scale Empirical Study. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bf649e9c-9d53-4e8c-a91b-f0a6b6aab733
Chicago Manual of Style (16th Edition):
Gerling, Jan (author). “Machine Learning for Software Refactoring: a Large-Scale Empirical Study.” 2020. Masters Thesis, Delft University of Technology. Accessed March 01, 2021.
http://resolver.tudelft.nl/uuid:bf649e9c-9d53-4e8c-a91b-f0a6b6aab733.
MLA Handbook (7th Edition):
Gerling, Jan (author). “Machine Learning for Software Refactoring: a Large-Scale Empirical Study.” 2020. Web. 01 Mar 2021.
Vancouver:
Gerling J(. Machine Learning for Software Refactoring: a Large-Scale Empirical Study. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 01].
Available from: http://resolver.tudelft.nl/uuid:bf649e9c-9d53-4e8c-a91b-f0a6b6aab733.
Council of Science Editors:
Gerling J(. Machine Learning for Software Refactoring: a Large-Scale Empirical Study. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:bf649e9c-9d53-4e8c-a91b-f0a6b6aab733
17.
MIN HUANG.
Data reduction with RSS methodology.
Degree: 2005, National University of Singapore
URL: https://scholarbank.nus.edu.sg/handle/10635/14616
Subjects/Keywords: DATA REDUCTION; RANKED SET SAMPLING
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APA (6th Edition):
HUANG, M. (2005). Data reduction with RSS methodology. (Thesis). National University of Singapore. Retrieved from https://scholarbank.nus.edu.sg/handle/10635/14616
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
HUANG, MIN. “Data reduction with RSS methodology.” 2005. Thesis, National University of Singapore. Accessed March 01, 2021.
https://scholarbank.nus.edu.sg/handle/10635/14616.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
HUANG, MIN. “Data reduction with RSS methodology.” 2005. Web. 01 Mar 2021.
Vancouver:
HUANG M. Data reduction with RSS methodology. [Internet] [Thesis]. National University of Singapore; 2005. [cited 2021 Mar 01].
Available from: https://scholarbank.nus.edu.sg/handle/10635/14616.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
HUANG M. Data reduction with RSS methodology. [Thesis]. National University of Singapore; 2005. Available from: https://scholarbank.nus.edu.sg/handle/10635/14616
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
NSYSU
18.
Lin, Shih-Bin.
A Study on Fuzzy Temporal Data Mining.
Degree: Master, Computer Science and Engineering, 2011, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151
► Data mining is an important process of extracting desirable knowledge from existing databases for specific purposes. Nearly all transactions in real-world databases involve items bought,…
(more)
▼ Data mining is an important process of extracting desirable knowledge from existing databases for specific purposes. Nearly all transactions in real-world databases involve items bought, quantities of the items, and the time periods in which they appear. In the past, temporal quantitative mining was proposed to find temporal quantitative rules from a temporal quantitative database. However, the quantitative values of items are not suitable to human reasoning. To deal with this, the fuzzy
set theory was applied to the temporal quantitative mining because of its simplicity and similarity to human reasoning. In this thesis, we thus handle the problem of mining fuzzy temporal association rules from a publication database, and propose three algorithms to achieve it. The three algorithms handle different lifespan definitions, respectively. In the first algorithm, the lifespan of an item is evaluated from the time of the first transaction with the item to the end time of the whole database. In the second algorithm, an additional publication table, which includes the publication date of each item in stores, is given, and thus the lifespan of an item is measured by its entire publication period. Finally in the third algorithm, the lifespan of an item is calculated from the end time of the whole database to its earliest time in the database for the item to be a fuzzy temporal frequent item within the duration. In addition, an effective itemset table structure is designed to store and get information about itemsets and can thus speed up the execution efficiency of the mining process. At last, experimental results on two simulation datasets compare the mined fuzzy temporal quantitative itemsets and rules with and without consideration of lifespans of items under different parameter settings.
Advisors/Committee Members: Cha-Hwa Lin (chair), Shyue-Liang Wang (chair), Chung-Nan Lee (chair), Tzung-Pei Hong (committee member).
Subjects/Keywords: fuzzy data mining; Fuzzy set; data mining; fuzzy temporal association rule; item lifespan
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APA (6th Edition):
Lin, S. (2011). A Study on Fuzzy Temporal Data Mining. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Lin, Shih-Bin. “A Study on Fuzzy Temporal Data Mining.” 2011. Thesis, NSYSU. Accessed March 01, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Lin, Shih-Bin. “A Study on Fuzzy Temporal Data Mining.” 2011. Web. 01 Mar 2021.
Vancouver:
Lin S. A Study on Fuzzy Temporal Data Mining. [Internet] [Thesis]. NSYSU; 2011. [cited 2021 Mar 01].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Lin S. A Study on Fuzzy Temporal Data Mining. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
19.
Sinsley, Gregory.
Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.
Degree: 2012, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/16157
► One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras,…
(more)
▼ One of the biggest challenges currently facing the robotics field is sensor
data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the
data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both
autonomous and intelligent operation. Another distinct fusion problem is that of fusing
data from teammates with
data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing
data gathered by robots with
data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing
data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions.
This thesis presents a system for fusing
data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized
data fusion. This is a foundational
data fusion issue, which has been very well studied. Important issues in centralized fusion include
data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods.
The second problem this thesis addresses is that of distributed
data fusion. Distributed
data fusion is a younger field than centralized fusion. The main issues in distributed fusion that are addressed are distributed classification and distributed tracking.
There are several well established methods for performing distributed fusion that are first reviewed. The chapter on distributed fusion concludes with a multiple unmanned vehicle collaborative test involving an unmanned aerial vehicle and an unmanned ground
vehicle.
The third issue this thesis addresses is that of soft sensor only
data fusion. Soft-only fusion is a newer field than centralized or distributed hard sensor fusion. Because of the novelty of the field, the chapter on soft-only fusion contains less background information and instead focuses on some new results in soft sensor
data fusion. Specifically, it discusses a novel fuzzy logic based soft sensor
data fusion method. This new method is tested using both simulations and field measurements.
The biggest issue addressed in this thesis is that of combined hard and soft fusion. Fusion of hard and soft
data is the newest area for research…
Advisors/Committee Members: Lyle Norman Long, Dissertation Advisor/Co-Advisor, William Kenneth Jenkins, Committee Chair/Co-Chair, David Miller, Committee Member, David J Hall, Committee Member, John Yen, Committee Member, Joseph Francis Horn, Committee Chair/Co-Chair.
Subjects/Keywords: sensor data fusion; information fusion; soft sensor data fusion; random set theory; particle filter
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APA (6th Edition):
Sinsley, G. (2012). Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16157
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Sinsley, Gregory. “Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.” 2012. Thesis, Penn State University. Accessed March 01, 2021.
https://submit-etda.libraries.psu.edu/catalog/16157.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Sinsley, Gregory. “Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.” 2012. Web. 01 Mar 2021.
Vancouver:
Sinsley G. Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. [Internet] [Thesis]. Penn State University; 2012. [cited 2021 Mar 01].
Available from: https://submit-etda.libraries.psu.edu/catalog/16157.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Sinsley G. Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/16157
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
20.
Mohebi, Ehsan.
Nonsmooth optimization models and algorithms for data clustering and visualization.
Degree: PhD, 2015, Federation University Australia
URL: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/77001
► Cluster analysis deals with the problem of organization of a collection of patterns into clusters based on a similarity measure. Various distance functions can be…
(more)
▼ Cluster analysis deals with the problem of organization of a collection of patterns into clusters based on a similarity measure. Various distance functions can be used to define this measure. Clustering problems with the similarity measure defined by the squared Euclidean distance have been studied extensively over the last five decades. However, problems with other Minkowski norms have attracted significantly less attention. The use of different similarity measures may help to identify different cluster structures of a data set. This in turn may help to significantly improve the decision making process. High dimensional data visualization is another important task in the field of data mining and pattern recognition. To date, the principal component analysis and the self-organizing maps techniques have been used to solve such problems. In this thesis we develop algorithms for solving clustering problems in large data sets using various similarity measures. Such similarity measures are based on the squared L
Doctor of Philosophy
Subjects/Keywords: Cluster analysis; Clustering problems; Cluster structure; Data set; High dimensional data visualization; Algorithms; Similarity measures
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APA ·
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Export
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Manager
APA (6th Edition):
Mohebi, E. (2015). Nonsmooth optimization models and algorithms for data clustering and visualization. (Doctoral Dissertation). Federation University Australia. Retrieved from http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/77001
Chicago Manual of Style (16th Edition):
Mohebi, Ehsan. “Nonsmooth optimization models and algorithms for data clustering and visualization.” 2015. Doctoral Dissertation, Federation University Australia. Accessed March 01, 2021.
http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/77001.
MLA Handbook (7th Edition):
Mohebi, Ehsan. “Nonsmooth optimization models and algorithms for data clustering and visualization.” 2015. Web. 01 Mar 2021.
Vancouver:
Mohebi E. Nonsmooth optimization models and algorithms for data clustering and visualization. [Internet] [Doctoral dissertation]. Federation University Australia; 2015. [cited 2021 Mar 01].
Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/77001.
Council of Science Editors:
Mohebi E. Nonsmooth optimization models and algorithms for data clustering and visualization. [Doctoral Dissertation]. Federation University Australia; 2015. Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/77001
University of Newcastle
21.
Jimenez, Francia.
The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.
Degree: PhD, 2019, University of Newcastle
URL: http://hdl.handle.net/1959.13/1400428
► Research Doctorate - Doctor of Philosophy (PhD)
In many application areas, the decision-making process is enhanced by the information obtained from analyzing data. In fact,…
(more)
▼ Research Doctorate - Doctor of Philosophy (PhD)
In many application areas, the decision-making process is enhanced by the information obtained from analyzing data. In fact, the process of improving digital products and services can be driven by insights from understanding complex relationships inside the data. Commonly to have a complete picture of the process, the data is obtained from multiple sources. Each source stores different type of data that it is essential for the specific data source. However, when we aggregate different sources, the new data can have some elements that can be considered as unreliable, irrelevant, or redundant for a specific problem. The previous challenge is known as Feature Selection (FS) and commonly presented during data integration. The k-Feature Set Problem (k-FS) is a problem in FS, that aims to find the minimum subset of features necessary to describe a dataset. Similarly, the (α; β)-k-Feature Set Problem (ABkFS) also aims to find the minimum subset of features, but in addition the subset of features needs to satisfy two conditions: α and β, where the α value is related with the differentiation power and the β value is related with the representation power of the subset of features. Commonly the ABkFS is used to reduce the number of features on datasets where the number of features is higher than the number of samples. This type of datasets can be found in bioinformatics where a few numbers of samples (e.g. corresponding to a set of biological samples obtained from individuals/patients) have their gene expression (features) measured in a quest to characterize a specific disease. In the literature, state-of-the-art feature selection techniques do not report good performance when analyzing this type of dataset because they use univariate tests which are commonly based on statistical measures across the samples. Currently, the ABkFS has been solved with exact models and also heuristics have been employed only based on single objective approach. However, there is a need to consider a multi-objective approach since the minimization of the number of features (usually required to achieve better generalization) “conspires” against the requirements of having a large value of α and β. This then constitutes a typical scenario in which the multi-objective approach is the most natural alternative. Many engineering solutions are developed using optimization techniques where we formally define an optimization problem which is composed by an objective function (or metric of interest) that we will optimize (minimize or maximize). A more realistic strategy of modeling optimization problems is assessing many objectives simultaneously, formally known as Multi-objective optimization problems (MOPs), where the main goal is to optimize multiple and possibly conflicting objectives. The conflict between two objectives functions is when improving the value of one of them worsen the second one. A special type of algorithms has been developed to solve MOP which are known as Multi-objective optimization…
Advisors/Committee Members: University of Newcastle. Faculty of Engineering & Built Environment , School of Electrical Engineering and Computing.
Subjects/Keywords: Feature Selection (FS); k-Feature Set Problem (k-FS); α; β)-k-Feature Set Problem (ABkFS); data integration
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APA ·
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MLA ·
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CSE |
Export
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Manager
APA (6th Edition):
Jimenez, F. (2019). The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1400428
Chicago Manual of Style (16th Edition):
Jimenez, Francia. “The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.” 2019. Doctoral Dissertation, University of Newcastle. Accessed March 01, 2021.
http://hdl.handle.net/1959.13/1400428.
MLA Handbook (7th Edition):
Jimenez, Francia. “The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.” 2019. Web. 01 Mar 2021.
Vancouver:
Jimenez F. The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. [Internet] [Doctoral dissertation]. University of Newcastle; 2019. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/1959.13/1400428.
Council of Science Editors:
Jimenez F. The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. [Doctoral Dissertation]. University of Newcastle; 2019. Available from: http://hdl.handle.net/1959.13/1400428
Vilnius Gediminas Technical University
22.
Pliuskuvienė, Birutė.
Adaptyvūs duomenų modeliai
projektavime.
Degree: Dissertation, Informatics
Engineering, 2008, Vilnius Gediminas Technical University
URL: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143724-43004
;
► Disertacijoje nagrinėjamos taikomųjų uždavinių, kurių duomenys išreikšti reliacinėmis aibėmis, sprendimus realizuojančių priemonių adaptyvumo problemos. Pagrindiniai tyrimo objektai yra adaptyvieji duomenų modeliai: duomenų išrinkimo modelis, duomenų…
(more)
▼ Disertacijoje nagrinėjamos taikomųjų
uždavinių, kurių duomenys išreikšti reliacinėmis aibėmis,
sprendimus realizuojančių priemonių adaptyvumo problemos.
Pagrindiniai tyrimo objektai yra adaptyvieji duomenų modeliai:
duomenų išrinkimo modelis, duomenų agregavimo modelis ir duomenų
apdorojimo projektavimo modelis. Darbo tikslas – sukurti
adaptyviąją duomenų apdorojimo projektavimo technologiją, kuri
leistų išrinkti, agreguoti ir apdoroti duomenis keičiant tik šią
technologiją sudarančių adaptyviųjų duomenų modelių formalių
išraiškų parametrus. Naudojant sukurtą technologiją skirtingiems
uždaviniams spęsti taikomas vienas ir tas pats duomenų apdorojimo
principas. Kitaip tariant, visą algoritmų ir juos realizuojančių
programini�� modulių sistemą galime pritaikyti skirtingiems
taikomojo pobūdžio uždaviniams spręsti. Tai leidžia sumažinti naujų
programinių priemonių kūrimo apimtis ir
sąnaudas.
The dissertation deals with the adaptivity
difficulties of the solutions implemented to solve applied problems
whose data is expressed as relational sets. The main objects of
research are adaptive data models: a data selection model, a data
aggregation model and a model for designing data processing. The
aim of the work is to create an adaptive technology for designing
data processing that would enable to perform data selection,
aggregation and processing by changing only the parameters of
formal expressions for the adaptive data models forming the
technology. While using the technology created for solving
different problems the same data processing principle is used. In
other words, the whole system of algorithms and program modules
implementing them can be adjusted for solving different problems of
applied nature. This allows to decrease the volume and expenses of
creating new software.
Advisors/Committee Members: Adomėnas, Petras Gailutis (Doctoral dissertation advisor), Baušys, Romualdas (Doctoral dissertation committee chair), Dzemydienė, Dalė (Doctoral dissertation opponent), Kulvietis , Genadijus (Doctoral dissertation opponent), Čaplinskas, Albertas (Doctoral dissertation committee member), Kaminskas, Vytautas (Doctoral dissertation committee member), Paliulis , Narimantas Kazimieras (Doctoral dissertation committee member), Simutis, Rimvydas (Doctoral dissertation committee member).
Subjects/Keywords: Reliacinė
aibė; Adaptyvieji duomenų
modeliai; Duomenų
transformaticija; Algoritminė duomenų
priklausomybė; Relation set; Adaptive data
models; Data
transformation; Algorithmic data
dependency
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APA ·
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MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Pliuskuvienė, B. (2008). Adaptyvūs duomenų modeliai
projektavime. (Doctoral Dissertation). Vilnius Gediminas Technical University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143724-43004 ;
Chicago Manual of Style (16th Edition):
Pliuskuvienė, Birutė. “Adaptyvūs duomenų modeliai
projektavime.” 2008. Doctoral Dissertation, Vilnius Gediminas Technical University. Accessed March 01, 2021.
http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143724-43004 ;.
MLA Handbook (7th Edition):
Pliuskuvienė, Birutė. “Adaptyvūs duomenų modeliai
projektavime.” 2008. Web. 01 Mar 2021.
Vancouver:
Pliuskuvienė B. Adaptyvūs duomenų modeliai
projektavime. [Internet] [Doctoral dissertation]. Vilnius Gediminas Technical University; 2008. [cited 2021 Mar 01].
Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143724-43004 ;.
Council of Science Editors:
Pliuskuvienė B. Adaptyvūs duomenų modeliai
projektavime. [Doctoral Dissertation]. Vilnius Gediminas Technical University; 2008. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143724-43004 ;
Vilnius Gediminas Technical University
23.
Pliuskuvienė, Birutė.
Adaptive data models in design.
Degree: PhD, Informatics
Engineering, 2008, Vilnius Gediminas Technical University
URL: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143940-41525
;
► In the dissertation the adaptation problem of the software whose instability is caused by the changes in primary data contents and structure as well as…
(more)
▼ In the dissertation the adaptation problem
of the software whose instability is caused by the changes in
primary data contents and structure as well as the algorithms for
applied problems implementing solutions to problems of applied
nature is examined. The solution to the problem is based on the
methodology of adapting models for the data expressed as relational
sets.
Disertacijoje nagrinėjama taikomųjų
uždavinių sprendimus realizuojančių programinių priemonių, kurių
nepastovumą lemia pirminių duomenų turinio, jų struktūrų ir
sprendžiamų taikomojo pobūdžio uždavinių algoritmų pokyčiai,
adaptavimo problema.
Advisors/Committee Members: Adomėnas, Petras Gailutis (Doctoral dissertation advisor), Baušys, Romualdas (Doctoral dissertation committee chair), Dzemydienė, Dalė (Doctoral dissertation opponent), Kulvietis, Genadijus (Doctoral dissertation opponent), Čaplinskas, Albertas (Doctoral dissertation committee member), Kaminskas, Vytautas (Doctoral dissertation committee member), Paliulis, Narimantas Kazimieras (Doctoral dissertation committee member), Simutis, Rimvydas (Doctoral dissertation committee member).
Subjects/Keywords: Relation set; Adaptive data
models; Data
transformation; Algorithmic data
dependency; Reliacinė
aibė; Adaptyvieji duomenų
modeliai; Duomenų
transformaticija; Algoritminė duomenų
priklausomybė
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APA ·
Chicago ·
MLA ·
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Export
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Manager
APA (6th Edition):
Pliuskuvienė, B. (2008). Adaptive data models in design. (Doctoral Dissertation). Vilnius Gediminas Technical University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143940-41525 ;
Chicago Manual of Style (16th Edition):
Pliuskuvienė, Birutė. “Adaptive data models in design.” 2008. Doctoral Dissertation, Vilnius Gediminas Technical University. Accessed March 01, 2021.
http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143940-41525 ;.
MLA Handbook (7th Edition):
Pliuskuvienė, Birutė. “Adaptive data models in design.” 2008. Web. 01 Mar 2021.
Vancouver:
Pliuskuvienė B. Adaptive data models in design. [Internet] [Doctoral dissertation]. Vilnius Gediminas Technical University; 2008. [cited 2021 Mar 01].
Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143940-41525 ;.
Council of Science Editors:
Pliuskuvienė B. Adaptive data models in design. [Doctoral Dissertation]. Vilnius Gediminas Technical University; 2008. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20080627_143940-41525 ;
University of South Africa
24.
Molefi, Zachariah Modise.
Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
.
Degree: 2014, University of South Africa
URL: http://hdl.handle.net/10500/18841
► Health practitioners collect health data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health…
(more)
▼ Health practitioners collect health
data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health programmes (District Health Plan 2012:6). Routine
data quality for health programmes monitoring need a collective intervention to ensure clear understanding for what
data to be collected at primary health care setting. The aim of the study is to explore the understanding of routine health
data, determine the use of routine
data and feedback mechanism at primary health care clinic setting. Quantitative descriptive research design was used to answer the research question on this research study. Structured
data collection questionnaire was used for the study to accomplish the research purpose and reach the study objectives. A total of 400 participants was sampled, and 247 responded. One of the findings was that the understanding of routine health
data by Health Practitioners was at 82.6% (% = f/n*100, f= 3242 and n= 3926).
Advisors/Committee Members: Makua, T. P (advisor).
Subjects/Keywords: Routine health data;
Data elements;
Health indicators;
Data quality;
Data validation;
Minimum data set;
Understanding of daily collected data;
Use of routine;
Information feedback presentation
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APA (6th Edition):
Molefi, Z. M. (2014). Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
. (Masters Thesis). University of South Africa. Retrieved from http://hdl.handle.net/10500/18841
Chicago Manual of Style (16th Edition):
Molefi, Zachariah Modise. “Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
.” 2014. Masters Thesis, University of South Africa. Accessed March 01, 2021.
http://hdl.handle.net/10500/18841.
MLA Handbook (7th Edition):
Molefi, Zachariah Modise. “Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
.” 2014. Web. 01 Mar 2021.
Vancouver:
Molefi ZM. Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
. [Internet] [Masters thesis]. University of South Africa; 2014. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/10500/18841.
Council of Science Editors:
Molefi ZM. Exploring the understanding of routinely collected data by the health practitioners in a primary health care setting
. [Masters Thesis]. University of South Africa; 2014. Available from: http://hdl.handle.net/10500/18841
Brno University of Technology
25.
Kříž, Radim.
Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation.
Degree: 2019, Brno University of Technology
URL: http://hdl.handle.net/11012/56094
► This work deals with the possibilities of interactive segmentation of medical image data using a ITK library and segmentation method level-set. It discusses the possibilities…
(more)
▼ This work deals with the possibilities of interactive segmentation of medical image
data using a ITK library and segmentation method level-
set. It discusses the possibilities of an interactive influencing of segmentation with user-defined edges and facilitate segmentation using modes allow automatic adjustment of parameters. An integral part of this work is user-friendly segmentation tool built on ITK library and segmentation method level-
set, which clearly demonstrates the possibilities of modes and added edges in practice. Design and implementation of this tool is also part of this work.
Advisors/Committee Members: Španěl, Michal (advisor), Štancl, Vít (referee).
Subjects/Keywords: metoda Level-set; segmentace; interaktivita; ITK; Qt; medicínská obrazová data; segmentace obrazu; uživatelsky přívětivé GUI; Level-set method; segmentation; interactivity; ITK; Qt; medical image data; image segmentation; user-friendly GUI
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APA (6th Edition):
Kříž, R. (2019). Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/56094
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Kříž, Radim. “Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation.” 2019. Thesis, Brno University of Technology. Accessed March 01, 2021.
http://hdl.handle.net/11012/56094.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Kříž, Radim. “Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation.” 2019. Web. 01 Mar 2021.
Vancouver:
Kříž R. Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/11012/56094.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Kříž R. Interaktivní segmentace medicínských obrazových dat: Interactive Medical Image Segmentation. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/56094
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
NSYSU
26.
Li, Yu.
Genetic-Fuzzy Mining with Type-2 Membership Functions.
Degree: Master, Computer Science and Engineering, 2015, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321
► Association rule mining is commonly utilized to extract useful information from given data. Since items are usually with quantities in real-world transaction databases, the fuzzy…
(more)
▼ Association rule mining is commonly utilized to extract useful information from given
data. Since items are usually with quantities in real-world transaction databases, the fuzzy
set theory is applied to many mining approaches for deriving fuzzy association rules. In the past, fuzzy mining mainly focused on type-1 membership functions. In this thesis, we attempt to use type-2 membership functions for mining. Type-2 fuzzy sets are generalization of type-1 fuzzy sets and are able to handle more uncertainty than type-1. An interval type-2 fuzzy association rule mining approach is first proposed in this thesis. Rules are mined by predefined interval type-2 membership functions. The quantitative transactions are transformed into fuzzy values according to the corresponding type-2 membership functions. The interval type-2 fuzzy values will be reduced to type-1 values by a centroid type reduction method in order to induce fuzzy association rules. Since membership functions are usually assumed to be known in advance in most of the fuzzy
data mining approaches, thus a GA-based type-2 fuzzy association rule mining is proposed to learn appropriate type-2 membership functions. The type-2 membership functions of each item are encoded as a chromosome and appropriate genetic operators are designed to find good solutions. In order to further enhance the quality of mining results, another GA-based representation, the 2-tuple linguistic representation, is also proposed. It adopts a different tuning mechanism and a modified evaluation function for the chromosomes to evolve. Experiments are also made to show the effectiveness of the proposed approaches. From the experimental results, the proposed approaches can mine more rules than using type-1 membership functions, and the qualities of rules are improved as well.
Advisors/Committee Members: Wen-yang Lin (chair), Tzung-Pei Hong (committee member), Ming-chao Chiang (chair), Chun-Hao Chen (chair).
Subjects/Keywords: genetic-fuzzy mining; association rule; data mining; type-2 fuzzy set; membership function
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APA ·
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Manager
APA (6th Edition):
Li, Y. (2015). Genetic-Fuzzy Mining with Type-2 Membership Functions. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Li, Yu. “Genetic-Fuzzy Mining with Type-2 Membership Functions.” 2015. Thesis, NSYSU. Accessed March 01, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Li, Yu. “Genetic-Fuzzy Mining with Type-2 Membership Functions.” 2015. Web. 01 Mar 2021.
Vancouver:
Li Y. Genetic-Fuzzy Mining with Type-2 Membership Functions. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Mar 01].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Li Y. Genetic-Fuzzy Mining with Type-2 Membership Functions. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Universiteit Utrecht
27.
Rosman, S.
Path planning for cyclists.
Degree: 2015, Universiteit Utrecht
URL: http://dspace.library.uu.nl:8080/handle/1874/320194
► In the field of path planning and crowd simulation, many models have been developed for simulating pedestrians, cars, and autonomous vehicles. However, no such models…
(more)
▼ In the field of path planning and crowd simulation, many models have been developed for simulating pedestrians, cars, and autonomous vehicles. However, no such models exist for bicycles. We present an analysis of the characteristics of bicycle riding and provide a model for simulating people riding bicycles. The method performs in real time, supports collision avoidance between cyclists and pedestrians, and handles dynamic obstacles such as parked cars.
Advisors/Committee Members: Geraerts, R.J., Stappen, A.F. van der.
Subjects/Keywords: bicycle; simulation; path planning; bicycle data set; simulating bicycles; cyclists; urban environments
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APA (6th Edition):
Rosman, S. (2015). Path planning for cyclists. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/320194
Chicago Manual of Style (16th Edition):
Rosman, S. “Path planning for cyclists.” 2015. Masters Thesis, Universiteit Utrecht. Accessed March 01, 2021.
http://dspace.library.uu.nl:8080/handle/1874/320194.
MLA Handbook (7th Edition):
Rosman, S. “Path planning for cyclists.” 2015. Web. 01 Mar 2021.
Vancouver:
Rosman S. Path planning for cyclists. [Internet] [Masters thesis]. Universiteit Utrecht; 2015. [cited 2021 Mar 01].
Available from: http://dspace.library.uu.nl:8080/handle/1874/320194.
Council of Science Editors:
Rosman S. Path planning for cyclists. [Masters Thesis]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/320194
University of Rochester
28.
Zhang, Yun; Qiu, Xing.
Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes.
Degree: PhD, 2020, University of Rochester
URL: http://hdl.handle.net/1802/35513
► Gene Set Enrichment Analysis (GSEA) is a powerful inferential tool that incorporates knowledge of a priori defined gene sets (e.g. molecular pathways) into the high-throughput…
(more)
▼ Gene Set Enrichment Analysis (GSEA) is a powerful
inferential tool that incorporates knowledge of a priori defined
gene sets (e.g. molecular pathways) into the high-throughput data
analyses. Knowledge-based gene sets are available in bioinformatics
resources such as the Kyoto Encyclopedia of Genes and Genomes
(KEGG) database. In databases built for general purposes,
multifunctional genes are assigned
to a number of pathways
simultaneously. For study-specific analyses (e.g. a specific
disease), these genes overlapped in multiple pathways are counted
multiple times no matter if their signals are associated with the
disease or not. However, most existing methods ignore the effect of
the overlapping genes in GSEA. In this thesis, we reveal the
substantial overlapping in KEGG pathways. We show that the
overlapping genes present pathway-specific activations under the
study-specific condition. Further, we computationally decompose the
overlapping genes using study-specific data and develop appropriate
similarity measures to assign their pathway memberships
empirically. Unlike the traditional binary membership (i.e. either
0 or 1), the empirical membership is quantified using continuous
weights. We design novel GSEA methods for two types of data:
time-course data and data with limited time points
(e.g.cross-sectional data). The former data contain rich temporal
information in individual subjects, which have the potential to
lead to personalized inference for precision medicine diagnosis.
The later data have simpler structure and are available from the
vast majority of studies. By using functional data analysis and
high-dimensional statistical learning tools, we build the
functional model and the cross-sectional model with respect to the
above data types. Upon obtaining the weights (a.k.a. empirical
memberships), we also derive two generalized hypothesis tests (i.e.
one parametric test and one nonparametric test) that accommodate
both weights and inter-gene correlation for the pathway-level test.
In contrast to the classical tests, these generalized tests not
only are more flexible, but also enormously reduce the
computational burden for various applications of high-throughput
data. For each new method, we conduct
simulation studies and
demonstrate through real data analyses. Lastly, all developed work
are implemented with efficient algorithms in R packages that are
publicly available
Subjects/Keywords: Elastic-net; Functional data analysis; Gene set enrichment analysis with empirical
memberships.
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APA ·
Chicago ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Zhang, Yun; Qiu, X. (2020). Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/35513
Chicago Manual of Style (16th Edition):
Zhang, Yun; Qiu, Xing. “Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes.” 2020. Doctoral Dissertation, University of Rochester. Accessed March 01, 2021.
http://hdl.handle.net/1802/35513.
MLA Handbook (7th Edition):
Zhang, Yun; Qiu, Xing. “Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes.” 2020. Web. 01 Mar 2021.
Vancouver:
Zhang, Yun; Qiu X. Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes. [Internet] [Doctoral dissertation]. University of Rochester; 2020. [cited 2021 Mar 01].
Available from: http://hdl.handle.net/1802/35513.
Council of Science Editors:
Zhang, Yun; Qiu X. Novel Statistical Methods for Gene Set Enrichment
Analysis with Empirical Memberships for Overlapping
Genes. [Doctoral Dissertation]. University of Rochester; 2020. Available from: http://hdl.handle.net/1802/35513
Jawaharlal Nehru University
29.
Jain, Rajni.
Rough set based decision tree induction for data
mining; -.
Degree: School of Computer and System Sciences, 2004, Jawaharlal Nehru University
URL: http://shodhganga.inflibnet.ac.in/handle/10603/35602
Available
Bibliography p.243-254 and Appendicies
p.A21-A28
Advisors/Committee Members: Minz, Sonajharia.Subjects/Keywords: Data mining; Rough set; Tree induction
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APA ·
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Manager
APA (6th Edition):
Jain, R. (2004). Rough set based decision tree induction for data
mining; -. (Thesis). Jawaharlal Nehru University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/35602
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jain, Rajni. “Rough set based decision tree induction for data
mining; -.” 2004. Thesis, Jawaharlal Nehru University. Accessed March 01, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/35602.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jain, Rajni. “Rough set based decision tree induction for data
mining; -.” 2004. Web. 01 Mar 2021.
Vancouver:
Jain R. Rough set based decision tree induction for data
mining; -. [Internet] [Thesis]. Jawaharlal Nehru University; 2004. [cited 2021 Mar 01].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/35602.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jain R. Rough set based decision tree induction for data
mining; -. [Thesis]. Jawaharlal Nehru University; 2004. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/35602
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of California – Merced
30.
Zumkehr, Andrew Lee.
Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes.
Degree: Environmental Systems, 2017, University of California – Merced
URL: http://www.escholarship.org/uc/item/6q39m8n3
► Carbonyl sulfide (COS or OCS) is emerging as a potentially important tracer of terrestrial biological carbon fluxes. Anthropogenic sources of atmospheric COS are a first…
(more)
▼ Carbonyl sulfide (COS or OCS) is emerging as a potentially important tracer of terrestrial biological carbon fluxes. Anthropogenic sources of atmospheric COS are a first order uncertainty for utilizing COS as a tracer of the carbon cycle. As anthropogenic COS is a confounding source of atmospheric COS when interpreting COS observations, incorrect estimates of anthropogenic COS sources can introduce large interpretation bias when attempting to infer carbon cycle fluxes. However, the current gridded estimate of anthropogenic sources of atmospheric COS is largely derived from data over three decades old and therefore is not likely to be representative of current atmospheric conditions. Here I address this critical knowledge gap by providing a new gridded estimate of anthropogenic COS sources derived from the most current industry activity and emissions factor data available and employ a more sophisticated approach for the spatial distribution of sources than presented in previous work. This new data set results in a very different picture of the spatial distribution of anthropogenic sources of COS and in a large upward revision in total global sources than estimated in previous work. The large missing source of atmospheric COS needed to balance the global budget of atmospheric COS has largely been attributed to an unknown ocean source in previous work. However, considering the large upward revision of anthropogenic COS sources estimated here, I present the hypothesis that anthropogenic sources may be a key component of the missing source of atmospheric COS. I present subsequent modeling scenarios to test this hypothesis and show that anthropogenic COS sources can explain observations of atmospheric COS as well as or better than enhanced ocean sources. Therefore, the data set of anthropogenic sources of COS presented here emerges as a key component of reducing interpretation bias when inferring carbon cycle fluxes using COS and for explaining the missing source of atmospheric COS and balancing the global COS budget (which has previously not been considered).
Subjects/Keywords: Environmental science; Atmospheric chemistry; Environmental engineering; Anthropogenic; Carbonyl Sulfide; data set; global; Sources
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APA ·
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Export
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Manager
APA (6th Edition):
Zumkehr, A. L. (2017). Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/6q39m8n3
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Zumkehr, Andrew Lee. “Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes.” 2017. Thesis, University of California – Merced. Accessed March 01, 2021.
http://www.escholarship.org/uc/item/6q39m8n3.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Zumkehr, Andrew Lee. “Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes.” 2017. Web. 01 Mar 2021.
Vancouver:
Zumkehr AL. Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes. [Internet] [Thesis]. University of California – Merced; 2017. [cited 2021 Mar 01].
Available from: http://www.escholarship.org/uc/item/6q39m8n3.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Zumkehr AL. Anthropogenic Sources of Carbonyl Sulfide: Implications for inverse analysis of process-level carbon cycle fluxes. [Thesis]. University of California – Merced; 2017. Available from: http://www.escholarship.org/uc/item/6q39m8n3
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
◁ [1] [2] [3] [4] [5] [6] [7] [8] ▶
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Open Access Theses and Dissertations